Spark job got stuck and no active tasks

Spark job got stuck and no active tasks

I was trying to train a ML pipeline (including a XGBoost classifier) on a very small data (i.e., 10Mb). During the training, certain MissingOutputLocation exceptions occurred, however, the Spark job got stuck with no active tasks, and never quit.

Re: Spark job got stuck and no active tasks

Hello Pola,

do you mind providing us the full XGBoost parameter map?

Did you try activating the "verbose mode" of XGBoost and see if something wrong is happening in the native code?

I usually increase verbosity from XGBoost by passing "silent = 0" in the param map, and calling Logger.getLogger("ml.dmlc.xgboost4j").setLevel(Level.INFO) (not sure if that's the right way to do it though).

I was trying to train a ML pipeline (including a XGBoost classifier) on a very small data (i.e., 10Mb). During the training, certain MissingOutputLocation exceptions occurred, however, the Spark job got stuck with no active tasks, and never quit.

Did you try activating the "verbose mode" of XGBoost and see if something wrong is happening in the native code?

I usually increase verbosity from XGBoost by passing "silent = 0" in the param map, and calling Logger.getLogger("ml.dmlc.xgboost4j").setLevel(Level.INFO) (not sure if that's the right way to do it though).

I was trying to train a ML pipeline (including a XGBoost classifier) on a very small data (i.e., 10Mb). During the training, certain MissingOutputLocation exceptions occurred, however, the Spark job got stuck with no active tasks, and never quit.

Did you try activating the "verbose mode" of XGBoost and see if something wrong is happening in the native code?

I usually increase verbosity from XGBoost by passing "silent = 0" in the param map, and calling Logger.getLogger("ml.dmlc.xgboost4j").setLevel(Level.INFO) (not sure if that's the right way to do it though).

I was trying to train a ML pipeline (including a XGBoost classifier) on a very small data (i.e., 10Mb). During the training, certain MissingOutputLocation exceptions occurred, however, the Spark job got stuck with no active tasks, and never quit.